熵和依赖的可变性:深度知识系统(SPK)和诱导熵联结作为联结密度可变性的度量

José-Luis Guerrero-Cusumano
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引用次数: 0

摘要

戴明的渊博知识体系(SPK)是一个在商业中创造、传播和应用知识的框架。它的一个基本原则是对变异的认识。SPK基于系统的方法,其中系统的每个部分都是相互关联的。过程控制旨在确定过程是否处于控制之中,即某些关键测量变量的分布是否稳定。复杂系统可以随时间变化,它们的可变性可以通过其熵和相互关系来测量。熵联结或相互关系被解释为由自变量的熵测量的独立性降低的度量。本文给出了多元t分布的熵联结的表达式,并引入了诱导熵联结的概念,作为联结密度变异性的度量。本文还提出了一种基于熵联结的不相关检验方法。以多变量控制图为例,用熵联法进行了分析。附录中提供了不同显著性水平下的检验表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy and the variability of dependence: System of profound knowledge (SPK) and induced entropy copula as a measure of variability for copula density
Deming’s System of Profound Knowledge (SPK) is a framework for creating, disseminating, and applying knowledge in business. One of its basic principles is the knowledge of variation. SPK is based on a systemic approach in which each part of the system is interconnected. Process control seeks to determine whether a process is in control, meaning whether the distribution of some critical measured variable is stable. Complex systems may vary through time and their variability can be measured by its entropy and its interrelatedness. The entropy copula or interrelatedness is interpreted as a measure of reduction of independence measured by the entropy of independent variables. This paper provides the expression of the entropy copula for multivariate t distribution and introduces the concept of induced entropy copula as a measure of variability for copula densities. A test for uncorrelatedness based on the entropy copula is also developed. A manufacturing example, using multivariate control chart, is analyzed using the entropy copula approach. Tables are provided in the appendix for testing at different significance levels.
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